通过近端集成传感实现微小连续机器人的三维力感知。
Cable-driven Continuum Robotics: Proprioception via Proximal-integrated Force Sensing
- 利用缆线张力与六轴力传感器融合感知
- 可同时估计接触力和接触位置,误差小于1.5N
- 适合微型手术机器人等高精度场景
微尺度连续体机器人在实现三维接触力感知方面面临显著挑战,主要源于结构微型化、非线性力学特性及传感器集成难题。本文提出一种基于近端集成力感知(即缆线张力与六轴力/扭矩传感器)的新方法,受手指腱-关节协同感知机制启发。通过建立人体组织与机器人组件的准生物仿生映射,将腱、关节与神经反馈的集成感知策略迁移至机器人系统;结合连续体机器人固有的结构约束,构建多模态感知策略,将力学非线性、材料非线性、运动状态与接触力间的复杂关系建模为优化问题,降低感知复杂度。实验验证表明该方法有效,可实现高精度的三维接触力与接触点定位,为更安全、智能的连续体机器人发展奠定基础,推动其在复杂环境中的临床应用。
原文摘要 · Abstract (English)
Micro-scale continuum robots face significant limitations in achieving three-dimensional contact force perception, primarily due to structural miniaturization, nonlinear mechanical, and sensor integration. To overcome these limitations, this paper introduces a novel proprioception method for cable-driven continuum robots based on proximal-integrated force sensing (i.e., cable tension and six-axis force/torque (F/T) sensor), inspired by the tendon-joint collaborative sensing mechanism of the finger. By integrating biomechanically inspired design principles with nonlinear modeling, the proposed method addresses the challenge of force perception (including the three-dimensional contact force and the location of the contact point) and shape estimation in micro-scale continuum robots. First, a quasi-bionic mapping between human tissues/organs and robot components is established, enabling the transfer of the integrated sensing strategy of tendons, joints, and neural feedback to the robotic system. Second, a multimodal perception strategy is developed based on the structural constraints inherent to continuum robots. The complex relationships among mechanical and material nonlinearities, robot motion states, and contact forces are formulated as an optimization problem to reduce the perception complexity. Finally, experimental validation demonstrates the effectiveness of the proposed method. This work lays the foundation for developing safer and smarter continuum robots, enabling broader clinical adoption in complex environments.
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